Diagnostic imaging of the spine of a patient is often useful for identifying disease or an injury to the spine itself or as a readily locatable landmark for other tissues. Present practice is to take and digitally store lots of data on a patient, including MR and CT images. You want to both compare each patient's data to his/her own data, and “pools” of data from other people. However, making sense of pictures taken at different times, and using different types of machines presents a problem which is presently beyond the reach of most automated systems. Additional complications are presented by variations in quality between images, incomplete images of the spine or neuro-axis (e.g., an image might not include top or bottom vertebrae), failure to adequately capture portions of the neuro-axis due to congenital defect, disease, injury or surgery, exceptional curvature of the spine exhibited in some individuals, and the existence of individuals having more or less than the highly prevalent 23 mobile pre-sacral vertebrae. Thus, analysis of images and prescription of additional data collection and treatment requires an extensively trained technician.
Unfortunately, even for skilled technicians, human error may occur due to the variability in the patient population or due to an oversight. The mistake may arise in incorrectly identifying vertebrae and discs in a diagnostic image. The mistake may arise in incorrectly visually identifying the corresponding vertebrae under the skin before performing a surgical or therapeutic (e.g., radiation) treatment. The mistake may arise in improperly identifying a normal, benign, or malignant condition because an opportunity is missed to correctly correlate information from a plurality of imaging systems (e.g., a type of tissue maybe determined if an MRI and a CT image could be properly correlated and analyzed).
Assuming the vertebrae and discs may be accurately identified in the diagnostic image, it is often helpful to be able to obtain a one-to-one correspondence between the readily visible and markable skin/surface and underlying structures or pathology detectable by a variety of imaging modalities. This may facilitate clinical correlation, XRT, image guided biopsy or surgical exploration, multimodality or interstudy image fusion, motion correction/compensation, and 3D space tracking. However, current methods, (e.g. bath oil/vitamin E capsules for MRI), have several limitations including single image modality utility requiring completely different and sometimes incompatible devices for each modality, complicating the procedure and adding potential error in subsequent multimodality integration/fusion. They require a separate step to mark the skin/surface where the localizer is placed and when as commonly affixed to the skin by overlying tape, may artifactually indent/compress the soft tissue beneath the marker or allow the localizer to move, further adding to potential error. Sterile technique is often difficult to achieve. Furthermore, it may be impossible to discriminate point localizers from each other or directly attain surface coordinates and measurements with cross sectional imaging techniques. In regards to the latter, indirect instrument values are subject to significant error due to potential inter-scan patient motion, nonorthogonal surface contours, and technique related aberrations which may not be appreciated as current multipurpose spatial reference phantoms are not designed for simultaneous patient imaging.
Limited coverage, resolution and contrast of conventional MRI localizers coupled with a high prevalence of spinal variance make definitive numbering difficult and may contribute to the risk of spinal intervention at the wrong level. Only 20% of the population exhibit the classic 7 cervical, 12 thoracic, 5 lumbar, 5 sacral, and 4 coccygeal grouping. For instance, 2-11% of individuals have a cephalad or caudal shift of lumbar-sacral transition, respectively resulting in 23 or 25 rather than the typical 24 mobile presacral vertebrae. Numbering difficulties are often heightened in patients referred for spine MRI. Such patients are more likely than the general population to have anomalies, acquired pathology, or instrumentation that distorts the appearance of vertebrae and discs. Moreover, these patients are often unable to he still within the magnet for more than a short period of time due to a high prevalence of back pain and spasms. Resultant intrascan motion confounds image interpretation and interscan motion renders scan coordinates and positional references unreliable.
Those difficulties and inadequacies in presently available technology can lead to significant problems. While data remains somewhat limited, various authors report an approximately 2-5% incidence of wrong level approach spinal intervention, with most cases involving the lower lumbar interspaces. Such surgical misadventures may lead to needless pain and suffering, as well as contribute to accelerating medical malpractice costs. The first multi-million dollar jury verdict for such a wrong level approach was awarded in 2002. In addition to potentially introducing errors, the use of human technicians to analyze images in present technology leads to significant delays and cost increases in diagnosis. For example, in the case of an image where insufficient information has been gathered by an initial scan, such as a scout scan, a human technician would examine the initial images, then prescribe new images, then would have to analyze the new images as well, leading to the necessity for images to be taken in multiple sessions over a longer period of time, a more complicated and expensive process than would be desirable.
Although several research techniques have been described to automate spine image analysis, to the inventors' best knowledge, none has successfully addressed the need for accurate and unambiguous numbering. In some cases, the inadequacies might be caused by simplifying assumptions based on normal spine anatomy which might not be appropriate for patients referred for spinal imaging (e.g., U.S. Pat. No. 6,853,741 to Ruth et al., which assumes that the distance between vertebrae is substantially constant). In others, inadequacies might stem from the fact that, even if an individual vertebra can be located, characterization of a vertebrae or disc is of limited clinical value if that structure cannot be accurately identified and named.
Consequently, a significant need exists for an improved approach to localizing and autoprescribing through multi-modal quick scans of the brain and/or spine. Furthermore, there is a need for enhancing personal medicine with a method of aligning skull and spine images.
Once one image set is autoprescribed, it would be further beneficial to correlate that image set with other types of imaging modalities that are also autoprescribed. One advantage is that calculations of changes over time for the same patient may quickly identify injury or disease. Another advantage is that different spectral emissions illicit different information about a tissue. Correlating between a plurality of imaging modalities, if a common tissue structure can be localized for each, may enable autodiagnosis as to whether the tissue is normal, benign or malignant. Consequently, it would be of a further advantage to extend spine autoprescription across multiple sources of diagnostic images.
Additionally, if a volume imaging data set is obtained it may be beneficial to have automated optimized 2-D reformations with labeling as desired to facilitate interpretation.